Today millions of college students are embracing digital learning technology. This was made especially clear by McGraw-Hill Education’s recent 2016 Digital Study Trends Survey. The results show just how central technology has become to the student experience:
- Four out of five students say digital learning technology is contributing to improvements in their grades.
- Eighty-eight percent say their smartphones have been helpful for studying.
- Most college students agree that digital learning technology should adapt to their unique way of learning (89 percent) and be individualized (80 percent).
- The majority of college students surveyed (61 percent) prefer to enroll in classes that use digital learning technology.
So where do we go from here?
We already have some early examples of what the future of technology in higher ed will look like, some great “pockets of the future.” The technology already has the power – in real classrooms, today – to positively affect the lives of students in a wide variety of learning contexts.
But unlocking the full potential of technology will require moving to the next level, which learning science shows is “mastery learning.”
Thirty years ago, Benjamin Bloom, one of America’s leading educational psychologists, wrote a seminal paper that is still one of the most important pieces of learning science available and something that is guiding our work at McGraw-Hill Education. He called it the “Two Sigma Problem.”
In his research he was able to show that by shifting from the standard “sage on a stage” format of classroom instruction to mastery learning, where students get continuous feedback and move forward only after demonstrating proficiency, average performance improved a full letter grade (from a C to a B, for example).
Bloom continued, showing that by adding a one-to-one tutoring environment on top of mastery learning, average performance improved two full grade levels. These are massive improvements.
In our current system, Bloom said, moving to a one-to-one tutoring environment would be all but impossible to achieve at scale – hence the title for his work, the “Two Sigma Problem.” But moving to a mastery learning environment is fully achievable if we could fully embrace the potential of technology. And that shift would dramatically improve outcomes for students globally.
As I said, digital learning technology is being used widely now, but students and instructors are only scratching the surface. If mastery learning is our next important goal, there are two key changes we must work toward to get there.
1) Helping instructors embrace data to its fullest extent. In short, this is the core of the value proposition of adaptive learning: it adds a data layer on top of content. Adaptive learning systems provide an incredible amount of data to instructors about how students are progressing, what they’re understanding and where they’re struggling. With millions of students using adaptive learning systems, we have the capacity with technology to mine that data and provide teachers with actionable insights that can help them do what they do best – teach. And do it even better. As yet, only the early adopters, a minority of instructors, are taking full advantage of these tools. We need to make them easier to use, and provide support for faculty to truly transform how they use data in support of great teaching.
2) Helping educators transform the delivery model so instruction becomes more fully differentiated. Adding powerful adaptive technology systems on top of the old sage-on-the-stage educational model can only go so far in improving performance. They key to moving toward a mastery learning model is helping instructors re-envision how they deliver instruction to take advantage of the arrows in their quivers. Most can agree it’s powerful for an instructor to have a real time view of her students’ performance 15 minutes before class starts – but what good is that if she already created a lesson plan and lecture? Mastery learning recognizes that every student learns at a different pace, so instruction needs to shift to a model with more frequent checkpoints, where instructors can intervene and teach at the point of need. The classroom is a place where failure is part of learning, and assessments are intrinsic to the daily work of learning. Students work in smaller groups and get more individual time with the instructor.
None of this work is easy – but it’s wholly achievable. For us, the starting point for the path forward is a close examination of the science of learning, and the science points us in the direction of mastery learning. The tools are available to us already – but now we need to do the hard work of helping instructors transform and enhance their practice. That’s something we will do even more of in 2017.